scholarly journals Estimation of Soil Loss Using Remote Sensing And GIS-Based Universal Soil Loss Equation In Northern Catchment of Lake Tana Sub-Basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Author(s):  
Veera Narayana Balabathina ◽  
Raju RP ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Lake Tana ◽  
Erosion Risk ◽  
Priority Areas ◽  
Erosion Rates ◽  
The Mean ◽  
Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

Soil erosion risk in Korean watersheds, assessed using the revised universal soil loss equation

2011 ◽  
Vol 399 (3-4) ◽  
pp. 263-273 ◽  
Author(s):  
Soyoung Park ◽  
Cheyoung Oh ◽  
Seongwoo Jeon ◽  
Huicheul Jung ◽  
Chuluong Choi
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Soil Loss Equation

Modeling potential erosion due to the Cerro Grande Fire with a GIS-based implementation of the Revised Universal Soil Loss Equation

2003 ◽  
Vol 12 (1) ◽  
pp. 85 ◽  
Author(s):  
Jay D. Miller ◽  
John W. Nyhan ◽  
Stephen R. Yool
Keyword(s):  
Soil Loss ◽  
Wildland Fire ◽  
National Laboratory ◽  
Thematic Mapper ◽  
Universal Soil Loss Equation ◽  
Burned Area ◽  
Los Alamos ◽  
Erosion Risk ◽  
Erosion Rates ◽  
Soil Loss Equation

Erosional processes directly influenced by wildland fire include reduction or elimination of above- ground biomass, reduction of soil organic matter, and hydrophobicity. High fuel loads promoted by decades of fire suppression in the U.S. increase the duration and intensity of burning, amplifying these effects. The Cerro Grande fire (6–31 May 2000) consumed approximately 15 000 hectares around and within the town of Los Alamos, New Mexico, USA. Private and public infrastructure including Los Alamos National Laboratory are at continuing risk due to increased threats of upstream erosion. We use a geographic information system (GIS) based implementation of the Revised Universal Soil Loss Equation (RUSLE) to model pre- and post-fire soil loss conditions and aid erosion risk analysis. Pre- and post-fire vegetation cover data layers were generated from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data. Based upon annual average rainfall amounts we estimate that subwatershed average pre-fire erosion rates range from 0.45 to 9.22 tonnes ha–1 yr–1 while post-fire erosion rates before watershed treatments range from 1.72 to 113.26 tonnes ha–1 yr–1. Rates are approximately 3.7 times larger for 50 year return interval rainfall amounts. It is estimated that watershed treatments including reseeding will decrease soil loss between 0.34 and 25.98% in the first year on treated subwatersheds. Immediately after the fire an interagency Burned Area Emergency Rehabilitation (BAER) team produced initial estimates of soil erosion. Our estimates of average erosion rates by subwatershed were in general larger than those initial estimates.

scholarly journals PENDUGAAN EROSI TANAH PADA LAHAN BEKAS TAMBANG BATU BINTANG SUB DAS BATANG KALULUTAN DAN SUNGAI IPUH KABUPATEN PADANG PARIAMAN

Jurnal Solum ◽  
2008 ◽  
Vol 5 (2) ◽  
pp. 88
Author(s):  
Adrinal Adrinal ◽  
Utri Luki ◽  
Pedri Kasman
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Erosion Risk ◽  
Erosion Prediction ◽  
Risk Rate ◽  
Soil Loss Equation

An erosion prediction using Universal Soil Loss Equation (USLE) was conducted from August 2006 to February 2007.  The research was aimed to predict amount of soil erosion and erosion risk rate of ex-obsidian mining of Kalulutan and Ipuh River, Padang Pariaman District.  The result showed that the highest soil erosion was predicted under ex-obsidian mining (45% slope) namely 2.593 t/ha/y and the lowest was found under mixed farm (3-8% slope), 4,95 t/ha/y. Erosion risk rate of ex-obsidian mining was very heavy whilst for mixed farm varied from light to very heavy.   Keyword: erosion prediction, ex-obsidian mining, Sub-catchments area

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